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Responsibilities: Undertake research on algorithms and data systems for next-generation data preparation and data cleaning for data analytics. Produce research papers, reports, and presentations as required by
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algorithms, including machine unlearning techniques, to enhance model robustness and reliability. Design and execute rigorous AI testing frameworks to assess and mitigate risks in AI systems. Collaborate with
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of the Environment (ASE), and the School of Electrical and Electronic Engineering (EEE), helping to develop algorithms and systems for disaster mapping and climate change in collaboration with space industries and
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of fairness, safety, and privacy in digital technologies. Key Responsibilities: Conduct research and development in trust technologies – translating algorithms into tools and frameworks and implementing working
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. The position is for one year, renewable subject to satisfactory performance. Successful candidates will conduct research and develop advanced deep learning and computer vision algorithms. Candidates are expected
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of the designed algorithms and systems. Help with research presentation works such as high-quality paper writing. Job Requirements: Preferably Bachelor’s degree in Computer Engineering, Computer
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Machine Learning algorithms Experience in conducting neuroimaging studies in educational contexts Experience in working with databases. Responsibilities Liaise with stakeholders (E.g. participating schools
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10 years of research experience. Proven track record in research and development of algorithms. Proficiency in algorithm development and programming skills using MATLAB or Phyton. Knowledge of machine
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. The focus will be on deriving efficient algorithms with provable statistical guarantees, using tools from: high-dimensional statistics, optimization, probability theory, approximation theory etc
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with data to experts and non-experts alike; and • Experience in sourcing, selecting, and applying machine learning techniques and designing algorithms that can be communicated to, and used by, non